Summary:
Crohn’s disease (CD) is lifelong inflammatory condition. We don’t know the exact causes in individual patients but we do know that genes, the environment within the gut and diet can all interact in this condition. Unfortunately, this disease is sometimes diagnosed in children. We have recruited hundreds of patients diagnosed in childhood and will use their anonymised samples and clinical information in this study. We plan to identify genetic changes in hundreds of genes known to be important in this disease. There is a new technology called next generation sequencing that allows us to do this efficiently. We also plan to detect all the products of metabolism – the biological pathways that help us get energy from fats, carbohydrates and proteins and use vitamins and minerals – in samples from the same patients using a very specialised machine called a nuclear magnetic resonance spectrometer! Both the genetic results and the metabolomics results generate enormous data sets. We need to use computer programs and mathematical models to help us interpret these data. We hope that by conducting both types of experiments in the same people and analysing the data together, that we will better understand any unusual findings. Our aim is always to help inform the clinical teams how to better diagnose and treat patients so they have a better quality of life. We want to help improve how children are treated so they grow properly, spend more time at school and less time in the clinic or hospital.

Sarah Ennis who is Professor of Genomics at the University of Southampton will lead the study and undertake the genetic analyses of the patients; Dr. Sandrine Claus, Associate Professor in Integrative Metabolism in the Department of food and Nutritional Sciences at University of Reading will lead on the NMR analysis of metabolites and; Prof Mark Beattie is consultant Paediatric Gastroenterologist/Honorary Professor of Paediatric Gastroenterology and Nutrition is the clinical lead for the study.

We will take DNA and plasma samples from about 200 children diagnosed with Crohn’s disease. We will analyse the two types of data (genetics and metabolomics) independently first and then merge all the important information together with details of how each child’s disease is behaving (e.g. what part of the gut is affected, how inflamed is the gut, does the patient get well on certain drugs, is the child growing normally). We will work with colleagues in mathematics at the University of Southampton to identify patterns in the data. We expect to find that although all the children are diagnosed with the same disease, that not everybody’s disease behaves the same. We want to identify key information that could help the medical team treat individual children differently according to how their own disease behaves.

We would love to identify very clear patterns in all of our first 200 children, but merging data in this way is a new field with lots of methods under development. We may only identify the strongest signals in a proportion of children. However, this would be a great start in getting experts from different disciplines coming together to make more sense out of the very sophisticated data they generate. Of course, we will need to follow up and confirm our findings in independent groups of patients to make sure they are real and robust. Because we have senior clinical staff on our team and we attend major national and international conferences about this disease, we will make sure the entire community treating these children get to hear about any important new breakthroughs.

I have been working in genetics for twenty years now. There have been enormous technological advances over the last decade and I want to see these used to the benefit of young patients diagnosed with IBD. There is lots we still don’t understand about IBD but we now have better data than ever before. We do need to work across disciplines in order to best interpret this information and translate our findings back to clinicians as quickly as possible.

We hope this project will give a better understanding of what is happening at the molecular level in patients diagnosed with CD. We expect to gain insight into how metabolism is working in patients and how metabolic changes interact with genetic changes. The modelling we apply in this project will pave the way to integrate even more data types. Ultimately, we want to be able to take in all information about a specific patients’ disease and use this to direct the best possible treatment.

I am delighted that this grant will enable us to integrate metabolomic and genomic analysis in children with Crohn’s disease. Applying and interpreting ‘big data’ approaches has enormous potential to understand disease dynamics.

Professor Sarah Ennis

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